On Thu, 25 Sep 2003 14:56:52 GMT, "seferiad" <[EMAIL PROTECTED]> wrote:
> I want to compare the variance of two "different" data sets for hypothesis > testing. If I assume the distributions of both data sets were normal, then > I simply apply the F-test. But I do not want to assume that the > distributions were derived from normal populations. If you want to compare the *variances*, the simplest F-test uses the ratio of the variances. That is sensitive, as you suggest (if that is what you are suggesting) to non-normality. The usual alternative is to compute the absolute deviations from the median (or from the mean, for convenience) and do a simple ANOVA on those numbers. Levene test. I wonder at the comment, about applying the F-test after assuming the normality; tests to compare sample variances are not of ordinary interest, except for ruling out problems with assumptions. I would never use the ratio-test in place of the Levene test, except as an informal guide while in the midst of exploratory analyses. > > I've searched and searched, but can't seem to find a clear explanation of > what is the appropriate replacement test (for the F test) for two non-normal > distributions. Can anyone help? Why is there so much discussion about > U-MannWhitney and other non-parametric tests that seem to focus more on > T-test replacements. At least that is what it seems like from my limited > perspective. The easiest tests, on two or more groups, are equivalent to performing a rank-transformation on the combined data; followed by ANOVA (or t-test) on the result: for small samples, the 'exact' results could be obtained by tabulation, if that were desired. - See the 1999 edition of Conover's Practical Nonparametric Statistics. Textbooks and articles focus on the two-group situation (t-test) because that is most common, and that is the easiest to describe and illustrate. If I am missing the point... please clarify. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
